Driving forwards, looking backwards

ONE of the world's leading data mining specialists says businesses are investing too much in generating data about customers and too little in analysing that data to ensure a positive return on investment and ensure profitable long-term customer relationships.

"Data is something companies drown in - it is not useful in itself. Analysis of data is what produces useable information to drive an enterprise forward," says Robert Schuyff of international data mining leader SPSS .

"Even where sufficient analysis of data occurs to translate data into meaningful decision-making information, that information is often historical rather than predictive.

“As a result, many managers are driving their businesses into the future with their eyes firmly fixed on the rear view mirror," says Mr Schuyff, who is managing director of SPSS Australasia and vice president SPSS Market Research (MR) Pacific Rim.

Established in Chicago in 1975, SPSS employs more than 9800 employees worldwide across 40 offices to develop software and service solutions, including analytical customer relationship management (CRM) solutions.

Mr Schuyff says true analytical software such as that developed by SPSS looks at the complete customer environment - as opposed to the data warehouses used by too many businesses that merely classify data and do little with it beyond confusing managers.

"Proper CRM systems - and we believe these are actually a minority of the systems currently in operation in the marketplace - place great importance on understanding what may happen in the future. They do this with sophisticated and flexible data mining techniques, such as propensity modeling.

"These provide the type of information that a business really needs to know - for example, a customer's propensity to buy a certain product set, a customer's propensity to buy more different products, a customer's propensity to leave you.

"This is the kind of predictive software that should be supplied within the analytical CRM area, because having models based on actual customer behaviour enables companies to accurately predict the future and gives them the power to change that future.

"Equally important is a company's ability to translate the conclusions drawn by its analysis into its operational systems. After all, there is no benefit to knowing that a high-value customer is about to leave unless a company's customer support centre is aware of it as well and is empowered to offer that customer incentives to stay.

“Similarly, there is no benefit to knowing what products a person is likely to buy on a website unless the company provides content that highlights those products.

"Successful CRM means far more than simply being better connected to customers - it means learning from those connections to enable more profitable interactions by predicting what customers will want next and inspiring their loyalty by helping them get it.

“It means tracking customer behaviour and using that data to maximise a customer's profitability and loyalty throughout the entire life cycle, from customer acquisition to retention.

"It's a fundamental fact that loyal customers are profitable. They purchase more; they cost less to sell to; and studies show they will refer on average five other people to your company. But how can you identify and cultivate loyal customers?

“By implementing analytical CRM solutions that employ data mining and analysis techniques that will help businesses to determine and deliver precisely what customers want.

"For example, by analysing customers who have left in the past, companies can develop models to predict which customers are likely to leave and when.

“Such models can also help a company determine which customers generate the most profits and therefore will cost the company more if they leave. The company can then create targeted retention strategies that help them avoid turnover."

Even with the end last year of the boom in business IT sales, the need for true analytical capability in CRM systems is increasing rather than declining.

"For business, there has been no respite in the flood of raw data flowing into companies - this is continuing to grow exponentially, year upon year, and today more than ever businesses need real solutions to handle it," says Mr Schuyff.

Customer relationship management has two components, an operational and an analytical component. Data mining lies at the heart of analytical CRM.

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